Research and Development wants help to determine new product ideas and pricing using existing product line as a benchmark.
We’ve identified several product gaps in the existing product line including:
Aluminum Over Mountain
Aluminum Triathalon
The Data Science Team has developed a pricing model that uses predictive analytics to estimate the price of the new bicycle models based on the existing fleet. This ensures that new models are priced comparatively to other similar bicycles.
New product prediction for 2 new models:
Trigger, Over Mountain with Aluminum Frame: $2,273
Slice, Triathalon with Aluminum Frame: $1,902
The current portfolio consits of 97 different bikes that were analyzed.
The visualization segments the full bicycle product line by category and frame material. This exposes two product gaps:
New Aluminum line of bikes in the Over Mountain Category
New Aluminum line of bikes in the Triathalon
New product prediction for 2 new models:
Trigger, Over Mountain with Aluminum Frame: $2,273
Slice, Triathalon with Aluminum Frame: $1,902
## [10:31:12] WARNING: amalgamation/../src/objective/regression_obj.cu:167: reg:linear is now deprecated in favor of reg:squarederror.
## [10:31:12] WARNING: amalgamation/../src/learner.cc:556: Loading model from XGBoost < 1.0.0, consider saving it again for improved compatibility
| New Model Attribute | Slice Al 1 | Trigger Al 1 |
|---|---|---|
| .pred | $1,902 | $2,273 |
| frame_material | Aluminum | Aluminum |
| category_2 | Triathalon | Over Mountain |
| model_base | Slice | Trigger |
| model_tier | Ultegra | Aluminum 1 |
| black | 0 | 0 |
| hi_mod | 0 | 0 |
| team | 0 | 0 |
| red | 0 | 0 |
| ultegra | 0 | 0 |
| dura_ace | 0 | 0 |
| disc | 0 | 0 |